Byron Yu's guest appearances

Byron Yu

Finding Genius Podcast

Center for Mind, Brain, and Culture

Stuart Duncan

David Berlinski

Derek Abbott

Lewis Cohen

Azra Raza

Angel Hack

Leah Segedie

Daniel Pompa

Sarah Hallberg

Beth Zupec-Kania

Adrienne Scheck

Tim Noakes

JJ Flizanes

Michael Alden

Eric Maisel

OwlTail

Steven Chase

Carnegie Mellon biomedical engineering professors Steven Chase and Byron Yu provide a stimulating overview of computer-brain interfaces that could eventually lead to stunning advances for those who have lost control of movement, due to injury or disease. The professors’ work is heavily focused on highly advanced computer brain interfaces that might allow a human to control robotic limbs, etc. simply by thinking. By studying the activity of neurons within the primary motor cortex, Chase and Yu seek to expand on recent successes to enable people who have ALS, stroke, or spinal cord injuries to take back control of some movement. As the professors explain, through this process, damaged tissue can be bypassed. They provide some details on the current clinic trial procedure that requires a surgical implantation of electrodes that essentially allows the patient to control functions via a plug. With as little as one hundred neurons, control can be achieved to some degree, but control of more neurons and further research will be necessary to perfect the computer brain interface to a level of sublime sophistication.  The Carnegie Mellon professors detail some of the areas of interest and desired applications of computer-brain interfaces. As they explain, for example, stroke victims may lose motor control of one side of their body. And researchers are looking at the possibility of sending control signals to the side of the body where control has been lost from the same side of the brain that is still successfully controlling the intact side of the body.  The work is complex and although thought can enable some control, this is not a complete solution, for as they explain, many of the computations utilized for basic tasks involving movement actually circumvent the thought process entirely. Thus, the conscious monitoring of motor control is somewhat limited. As the professors explain, reanimating limbs would be the ideal scenario, but stimulation of muscles often directly impacts fast twitch fibers more than slow twitch fibers, which, unfortunately, leads to rapid muscle fatigue. Therefore, much more research is needed to perfect these complex solutions to extremely complex problems. In their opinion, the next decade will deliver clinical translations, as devices will be used for therapy for select types of patients, for control of spelling devices, for control of cursors to allow for computer usage, and also for wheelchair control. However, it may be a long time before advanced robotic control is delivered such that the computer brain interface can offer absolute control of robotic limbs, possibly with sensory input that is sent back to the brain. And ultimately the Carnegie Mellon professors hope that brain-computer interfaces will allow researchers to learn and understand the intricate workings of the human brain. 

Carnegie Mellon biomedical engineering professors Steven Chase and Byron Yu provide a stimulating overview of computer-brain interfaces that could eventually lead to stunning advances for those who have lost control of movement, due to injury or disease. The professors’ work is heavily focused on highly advanced computer brain interfaces that might allow a human to control robotic limbs, etc. simply by thinking. By studying the activity of neurons within the primary motor cortex, Chase and Yu seek to expand on recent successes to enable people who have ALS, stroke, or spinal cord injuries to take back control of some movement. As the professors explain, through this process, damaged tissue can be bypassed. They provide some details on the current clinic trial procedure that requires a surgical implantation of electrodes that essentially allows the patient to control functions via a plug. With as little as one hundred neurons, control can be achieved to some degree, but control of more neurons and further research will be necessary to perfect the computer brain interface to a level of sublime sophistication.  The Carnegie Mellon professors detail some of the areas of interest and desired applications of computer-brain interfaces. As they explain, for example, stroke victims may lose motor control of one side of their body. And researchers are looking at the possibility of sending control signals to the side of the body where control has been lost from the same side of the brain that is still successfully controlling the intact side of the body.  The work is complex and although thought can enable some control, this is not a complete solution, for as they explain, many of the computations utilized for basic tasks involving movement actually circumvent the thought process entirely. Thus, the conscious monitoring of motor control is somewhat limited. As the professors explain, reanimating limbs would be the ideal scenario, but stimulation of muscles often directly impacts fast twitch fibers more than slow twitch fibers, which, unfortunately, leads to rapid muscle fatigue. Therefore, much more research is needed to perfect these complex solutions to extremely complex problems. In their opinion, the next decade will deliver clinical translations, as devices will be used for therapy for select types of patients, for control of spelling devices, for control of cursors to allow for computer usage, and also for wheelchair control. However, it may be a long time before advanced robotic control is delivered such that the computer brain interface can offer absolute control of robotic limbs, possibly with sensory input that is sent back to the brain. And ultimately the Carnegie Mellon professors hope that brain-computer interfaces will allow researchers to learn and understand the intricate workings of the human brain.

Mind Control – Steven Chase and Byron Yu, Professors of Biomedical Engineering, Carnegie Mellon University – Computer Brain Interfaces That Could Allow Control of Body Movement Through Thought

Most sensory, cognitive, and motor functions rely on the interaction among many neurons. To analyze the activity of many neurons together, many groups are now adopting advanced statistical methods, such as dimensionality reduction. In this talk, I will first describe how dimensionality reduction can be used in a closed-loop experimental setting to understand how learning is shaped by the underlying neural circuitry. Then, I will describe a novel latent variable model that extracts a subject's internal model during sensorimotor control. NEUROSCIENCE WORKSHOP: Dimensionality Reduction Friday, October 30, 2015 Saturday, October 31, 2015

Most sensory, cognitive, and motor functions rely on the interaction among many neurons. To analyze the activity of many neurons together, many groups are now adopting advanced statistical methods, such as dimensionality reduction. In this talk, I will first describe how dimensionality reduction can be used in a closed-loop experimental setting to understand how learning is shaped by the underlying neural circuitry. Then, I will describe a novel latent variable model that extracts a subject's internal model during sensorimotor control. NEUROSCIENCE WORKSHOP: Dimensionality Reduction Friday, October 30, 2015 Saturday, October 31, 2015

Neuroscience Workshop/Lecture (1 of 5) | Byron Yu | Dimensionality Reduction of Large-Scale Neural Recordings during Sensorimotor Control